Avaliação genética de uma população multirracial Angus-Nelore

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Prestes, Alan Miranda
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
Brasil
Zootecnia
UFSM
Programa de Pós-Graduação em Zootecnia
Centro de Ciências Rurais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufsm.br/handle/1/11335
Resumo: The objective of this study was to evaluate the best model for the genetic evaluation for the trait average daily gain of weaning to post weaning (ADGWP), of a multiple-breed Nellore and Angus population, comprised of 49.634 animals sired by 34.006 dams and 793 sire, born between 1986 and 2015. The genetic evaluation for this population was performed through the methodology of Bayesian inference with the animal model and the criteria of choice were the Number of Parameters (Np), Deviance Information (DIC) and the conditional predictive ordinate (CPO). In the first chapter three models were tested: Traditional Animal Model (TAM), Multiple-Breed Animal Model With (MBAMW) and without segregation (MBAMWS). Based on the selection criteria, the MBAMW was chosen because it presents better adjustments, besides presenting the smallest number of parameters, thus reducing the computational demand. In the second chapter, heteroscedastic multiple-breed models (HMBM) were tested. A 2×2 factorial scheme of two residual variance models (homoscedastic (HO) or heteroscedastic (HE)) was used based on two distributive assumptions (Gaussian (G) and Student’s t (T)). The HMBM-T-HE presented the best fit for the population in question. The Spearman's ordering correlations of the breeding values predicted for the sires were high when all animals were considered (0.93 to 0.99). However, when these sires were separated in TOP (10%) these correlations were reduced drastically (from 0.05 to 0.96). These results support the implementation of robust multibreed models that account for sources of heteroscedasticity to increase the accuracy of genetic assessments of multiple-breed populations.